Numerical Tensor Methods
Tensor Trains in Mathematics and Computer Science
Series:De Gruyter Textbook
- The first textbook in this vibrant field of numerics.
- Methods enabling numerical solutions to notoriously difficult high-dimensional problems.
- Numerics examples are available as a Jupyter notebook online.
Aims and Scope
Covering both theoretical foundations and applications in mathematics and engineering, this graduate textbook introduces numerical, tensor-based methods for tackling high-dimensional problems. Concepts known as tensor trains, matrix product states or hierarchical tensor networks have a range of applications in differential equations, multidimensional integration, machine learning, condensed matter physics, and theoretical chemistry.
- 24.0 x 17.0 cm
- xvi, 200 pages
- 20 Fig.
- Type of Publication:
- Professional Book